Linux直接执行语句:nlg-eval --setup Windows进入文件夹中后执行语句:python bin\nlg-eval --setup 还是因为网络的问题,下的会特别慢。手动下载所有的文件到本地。需要下载的文件列表在刚刚下载好的安装包的"./nlg-eval/bin/nlg-eval"文件中可以找到,一共有10个文件,亲测都可以使用手动下载完成,大概7个GB。以...
nlg-eval --setup If you're setting this up from the source code or you're on Windows and not using a Bash terminal, then you might get errors aboutnlg-evalnot being found. You will need to find thenlg-evalscript. Seeherefor details. ...
背景:需要计算Meteor分数,选择使用nlg-eval库,链接为: https://github.com/Maluuba/nlg-eval使用该库,发现计算Meteor时出错,显示: self.meteor_p不存在 分析: 通过代码定位,初步确定为Meteor.py里面的 se…
, author='Shikhar Sharma, Hannes Schulz, Justin Harris', author_email='shikhar.sharma@microsoft.com, hannes.schulz@microsoft.com, justin.harris@microsoft.com', url='https://github.com/Maluuba/nlg-eval', packages=find_packages(), include_package_data=True, scripts=['bin/nlg-eval'], install...
(LLMs) as reference-free metrics for NLG evaluation, which have the benefit of being applicable to new tasks that lack human references. However, these LLM-based evaluators still have lower human correspondence than medium-size neural evaluators. In this work, we present G-Eval...
PsyDuck/nlg-eval forked from 马乐驰/nlg-eval 确定同步? 同步操作将从 马乐驰/nlg-eval 强制同步,此操作会覆盖自 Fork 仓库以来所做的任何修改,且无法恢复!!! 确定后同步将在后台操作,完成时将刷新页面,请耐心等待。 删除在远程仓库中不存在的分支和标签 同步Wiki (当前仓库的 wiki 将会被覆盖!) ...
2017. SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs and News. In Proceedings of the 11th International Workshop on Semantic Evaluations (SemEval-2017), pages 519- 535, Vancouver, Canada. ACL.Chung-Chi Chen, et al. 2017. Nlg301 at semeval- 2017 task 5: ...
nlg-eval8KB nlgeval __init__.py13KB pycocoevalcap AutoCoder多语言自动代码生成器 可以生成多种语言(如:ASP、C#、C++BUILDER、DELPHI、JAVA、JSP、PHP、VB、VC.NET……),不同层次结构(B/S、C/S、n-tiger……),基于不同数据库(ORAC 352019-05-04 ...
使用NLG-Eval需要依赖的数据包Tp**wd 上传822.24MB 文件格式 zip 使用NLG_Eval需要依赖的数据包 点赞(0) 踩踩(0) 反馈 所需:1 积分 电信网络下载 1124728943189109小马模拟器.apk 2025-04-02 03:42:04 积分:1 Copyright © 2015 - 2025 https://www.coder100.com/ All rights reserved. 备案号:浙...
This workshop is intended as a discussion platform on the status and the future of the evaluation of Natural Language Generation systems. Among other topics, we will discuss current evaluation quality, human versus automated metrics, and the development of shared tasks for NLG evaluation. The work...